1. Field of the Invention
The present invention relates to a multimedia-object-retrieving method and system, particularly to a multimedia-object-retrieval method and system for retrieving similar multimedia objects in accordance with feature values of the multimedia objects.
2. Description of the Related Art
Multimedia-object data for images, movies, voices, and music serving as digital data is recently being used in various application.
For example, in the case of data for expressing a three-dimensional object, the following are actively used: CAD, merchandise advertisements and digital archives obtained by converting archaeological assets and art objects into three-dimensional object data.
Moreover, much digital image data and digital music data are exchanged through the Internet.
Because these data use have increased, requests for efficiently managing data and efficiently retrieving the data requested by users are raised.
To respond to these requests, various techniques are proposed. Also for the similar-object-retrieval technique, many retrieval methods are proposed in each of which characteristics of a multimedia object are calculated as feature values expressed by numerical values to use a multidimensional vector constituted by these feature values.
In the case of the similar-object retrieval using feature values, a user designates an object desired as a retrieval result and compares the feature value of the object with that of an object entered in a database and thereby, the user can retrieve similar objects.
In this case, it is generally performed to set a weighting factor for expressing the importance of each feature value.
That is, by properly setting a weighting factor so as to reflect the purpose and taste of a user, it is possible to retrieve objects whose colors are different from each other but whose shapes are similar.
A method is proposed which performs efficient retrieval by properly setting the above weighting factor.
For example, Jpn. Pat. Appln. KOKAI Publication No. 7-21198 discloses an image-retrieval method making it possible to adjust the weighting factor of each feature value when calculating similarity by designating a plurality of images similar to a necessary image and a plurality of images not similar to the necessary image.
Moreover, Jpn. Pat. Appln. KOKAI Publication No. 9-101970 discloses an image-retrieval method and an image-retrieval apparatus making it possible to adjust the weighting factor of each feature value when calculating similarity by setting a plurality of images similar to a desired image and a plurality of images not similar to the desired image.
Furthermore, in the case of the above image-retrieval method and image-retrieval apparatus, it is possible to designate a plurality of images similar to a desired image and a plurality of images not similar to the desired image, again out of images displayed as a result of retrieving similar images.
Thus, it is possible to adjust a weighting factor so that it becomes a more-proper weighting factor by repeating the operation of using the result of retrieving similar images as a new input.
Moreover, Jpn. Pat. Appln. KOKAI Publication No. 10-154149 discloses a similar-object-retrieval method and apparatus using means for adding an object probably similar to a reference object designated by a user out of a group of output sample objects and capable of adjusting a weighting factor so that it approaches a more proper weighting factor.
In the case of the above conventional method, it is necessary to classify purposed objects into only two types of whether they are similar to a desired object or not.
However, because most objects respectively have a portion similar to a desired object and a portion not similar to the desired object, it is difficult to clearly classify them into similar objects and not-similar objects.
For example, in the case of the “image-retrieval method” disclosed in Jpn. Pat. Appln. KOKAI Publication No. 7-21198, it is possible to designate a previously presented image as an image similar to a necessary image or an image not similar to the necessary image.
However, it is not easy to determine whether every independent image is similar to a necessary image except for the case in which the image is very similar to a desired image or it is greatly different from the desired image.
Moreover, in the case of the “image-retrieval method and image-retrieval apparatus” disclosed in the above Jpn. Pat. Appln. KOKAI Publication No. 9-101970 and the “similar-object-retrieval method and apparatus” disclosed in the above Jpn. Pat. Appln. KOKAI Publication No. 10-154149, the same difficulty as the above is present in the process for determining whether an image or object is similar to a desired one.
For example, however, it is not very difficult to compare two objects and determine which one is similar to a desired object.
This is because it is allowed to determine only the relative similarity between two objects instead of determining absolute similarities between independent objects.